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In scooter/motorbike engines coherent and stable tumble motion generation is still considered an effective mean in order to both reduce engine emissions and promote higher levels of combustion efficiency. The scientific research also assessed that squish motion is an effective mean for speeding up the combustion in a combustion process already fast. In a previous technical paper the authors demonstrated that for an engine having a high C/D ratio the squish motion is not only not necessary but also detrimental for the stability of the tumble motion itself, because there is a strong interaction between these two motions with the consequent formation of secondary vortices, which in turn penalizes the tumble breakdown and the turbulent kinetic energy production.

In this paper three-dimensional Large Eddy Simulations (i.e., LES) by using a PLIC-VOF method have been adopted to investigate the atomization process of round liquid jets issuing from automotive multi-hole injector-like nozzles. LES method is used to compute directly the effect of the large flow structure, being the smallest one modelled. A mesh having a cell size of 4 μm was used in order to derive a statistics of the detached liquid structures, i.e. droplets and ligaments. The latter have been identified by using an algorithm coded by authors. Cavitation modeling has not been included in the present computations. Two different mean injection nozzle flow velocities of 50 m/s and 270 m/s, corresponding to two mean nozzle flow Reynolds numbers of 1600 and 8700, respectively, have been considered in the calculations as representative of laminar and turbulent nozzle flow conditions.

A flash evaporation model is being developed to capture the effects of bubble nucleation and growth inside multi-hole injector nozzles to investigate the flash evaporation in fuel injector sprays in Gasoline Direct Injection (GDI). The 1D flash evaporation model is a key tool for providing the 3D Eulerian-Eulerian or Lagrangian spray simulation model with the right droplet size in order to properly predict the effect of degree of superheating on mixture formation. Super heating conditions are likely to be found under partial load conditions in GDI applications or they might be deliberately induced to enhance fuel atomization and vaporization. A quasi-1D nozzle flow model has been developed to help quantifying the effects of main physical and geometrical parameters in promoting fuel flash evaporation. This model is based on an weakly compressible homogenous two-phase mixture assumption. A non-equilibrium model is used to predict the vapour formation rate along the nozzle.

Traditional User/Maintenance Manuals provide useful information when dealing with simple machines. However, when dealing with complex systems of systems and highly miniaturized technologies, like UAVs, or with machines with millions of parts, a commercial aircraft is a case in point, new technologies taking advantage of Augmented Reality can rapidly and effectively support the maintenance operations. This paper presents a User/Maintenance Manual based on Augmented Reality to help the operator in the detection of parts and in the sequence to be followed to assemble/disassemble systems and subsystems. The proposed system includes a handheld device and/or an head mounted display or special goggles, to be used by on-site operators, with software management providing data fusion and overlaying traditional 2D user/maintenance manual information with an augmented reality software and appropriate interface.

The laminar burning speed is an important intrinsic property of an air-fuel mixture determining key combustion characteristics such as turbulent flame propagation. It is a function of the mixture composition (mixture fraction and residual gas mass fraction) and of the thermodynamic conditions. Experimental measurements of Laminar Flame Speeds (LFS) are common in literature, but initial pressure and temperature are limited to low values due to the test conditions: typical pressure values for LFS detection are lower than 25 bar, and temperature rarely exceeds 550 K. Actual trends in spark ignition engines are to increase specific power output by downsizing and supercharging, thus the flame front involves even more higher pressure and temperature since the beginning of combustion.

Obtaining and maintaining a stratified charge in a practical engine is a difficult problem. Consequently, many approaches have been proposed and reported in the scientific and patent literature. In attempting to assess the most profitable approach for future development work, it is important to group together similar approaches so that one can study their performance as a group. Making such a classification has the additional advantage of helping to standardize terminology used by different investigators. With this thought in mind, a literature study was made and a proposed classification chart prepared for the different engine combustion systems reported in the literature. For the sake of completeness, the finally proposed classification chart includes homogeneous combustion engines as well as heterogeneous combustion engines. Because of their similarity of combustion, rotary engines such as the Wankel engine are considered as “reciprocating” although gas turbines are not included.

Electrification is the well-accepted solution to address carbon emissions and modernize vehicle controls. Batteries play a critical in the journey of electrification and modernization with battery voltage prediction as the foundation for safe and efficient operation. Due to its strong dependency on prior information, battery voltage was estimated with recurrent neural network methods in the recent literatures exploring a variety of deep learning techniques to estimate battery behaviors. In these studies, standard recurrent neural networks, gated recurrent units, and long-short term memory are popular neural network architectures under review. However, in most cases, each neural network architecture is individually assessed and therefore the knowledge about comparative study among three neural network architecture is limited. In addition, many literatures only studied either the dynamic voltage response or the voltage relaxation.

A computer program which rapidly calculates the equilibrium mole fractions and the partial derivatives of the mole fractions with respect to temperature, pressure and equivalence ratio for the products of combustion of any hydrocarbon fuel and air is described. A subroutine is also given which calculates the gas constant, enthalpy, internal energy and the partial derivatives of these with respect to temperature, pressure and equivalence ratio. Some examples of the uses of the programs are also given.

The performance optimization of modern Spark Ignition engines is limited by knock occurrence: heavily downsized engines often are forced to work in the Knock-Limited Spark Advance (KLSA) range. Knock control systems monitor the combustion process, allowing to achieve a proper compromise between performance and reliability. Combustion monitoring is usually carried out by means of accelerometers or ion sensing systems, but recently the use of cylinder pressure sensors is also becoming frequent in motorsport applications. On the other hand, cylinder pressure signals are often available in the calibration stage, where SA feedback-control based on the pressure signal can be used to avoid damages to the engine during automatic calibration. A predictive real-time combustion model could help optimizing engine performance, without exceeding the allowed knock severity.

One of the major challenges in multiobjective, multidisciplinary design optimization (MDO) is the long computational time required in evaluating the new designs' performances. To shorten the cycle time of product design, a data mining-based strategy is developed to improve the efficiency of heuristic optimization algorithms. Based on the historical information of the optimization process, clustering and classification techniques are employed to identify and eliminate the low quality and repetitive designs before operating the time-consuming design evaluations. The proposed method improves design performances within the same computation budget. Two case studies, one mathematical benchmark problem and one vehicle side impact design problem, are conducted as demonstration.

The European Commission is going to publish the new Euro7 standard shortly, with the target of reducing the impact on pollutant emissions due to transportation systems. Besides forcing internal combustion engines to operate cleaner in a wider range of operating conditions, the incoming regulation will point out the role of On-Board Monitoring (OBM) as a key enabler to ensure limited emissions over the whole vehicle lifetime, necessarily taking into account the natural aging of involved systems and possible electronic/mechanical faults and malfunctions. In this scenario, this work aims to study the potential of data-driven approaches in detecting emission-relevant engine faults, supporting standard On-Board Diagnostics (OBD) in pinpointing faulty components, which is part of the main challenges introduced by Euro7 OBM requirements.

Added masses computation is a crucial aspect to be considered when the density of a body moving in a fluid is comparable to the density of the fluid displaced: added mass can be defined as the inertia added to a system because an accelerating or decelerating body displaces some volume of neighboring fluid as it moves through it. The motion of vehicles like airships and ships can be addressed only by keeping into account the effect of added masses, while in case of aircrafts and helicopters this contribution is usually neglected. Lighter Than Air flight simulation, unmanned airships flight control system, airships flight dynamics are typical applications in which added masses are fundamental to achieve an effective and realistic modeling. A panel based method using the mesh of an airship external shape is developed to account for the added massed.

The results of two derivations relating to the fuel economy of hybrid-electric vehicles (vehicles which employ both a heat engine and electric drive system) are presented and their use is illustrated through the examples of the University of Wisconsin and TRW Systems Group hybrid-electric vehicles. The method of mileage estimation employs a specific fuel-consumption versus torque-speed map for the heat engine under study and knowledge of the hybrid-vehicle dynamics and road-load power. The method is easily extended to estimation of emission reductions through use of specific-emission-production versus torque-speed maps and is applicable to hybrid vehicles with other than electrical energy-storage systems.

This paper presents a methodology for the 3D CFD simulation of the intake and compression processes of four stroke internal combustion engines.The main feature of this approach is to provide very accurate initial conditions by means of a cost-effective initialization step. Calculations are applied to a low stroke-to-bore SI engine, operated at full load and maximum engine speed. It is demonstrated that initial conditions for this kind of engines have an important influence on flow field development, particularly in terms of mean velocities close to the firing TDC. Simulation results are used to discuss the choice of a set of parameters for the flow field characterization of low stroke-to-bore engines, as well as to provide an insight into the flow patterns during the overlapping period.

Analytical models (math or computer simulation models) are typically built on the basis of many assumptions and simplifications and hence model prediction could be inaccurate in intended applications. Model validation is thus critical to quantify and improve the degree of accuracy of these models. So far, little work considers model validation for various design configurations so that model prediction is accurate in the intended design space. Furthermore, there is a lack of effective approaches that can be used to quantify model accuracy considering different number of experimental data. To overcome these limitations, objective of this paper is to develop a model validation approach for various design configurations with a reference metric for model accuracy check considering different number of experimental data.

Particle swarm optimization (PSO) is a relatively new stochastic optimization algorithm and has gained much attention in recent years because of its fast convergence speed and strong optimization ability. However, PSO suffers from premature convergence problem for quick losing of diversity. That is to say, if no particle discovers a new superiority position than its previous best location, PSO algorithm will fall into stagnation and output local optimum result. In order to improve the diversity of basic PSO, design of experiment technique is used to initialize the particle swarm in consideration of its space-filling property which guarantees covering the design space comprehensively. And the optimization procedure of PSO is divided into two stages, optimization stage and improving stage. In the optimization stage, the basic PSO initialized by Optimal Latin hypercube technique is conducted.

Pending reductions in light duty vehicle PM emissions standards from 10 to 3 mg/mi and below will push the limits of the gravimetric measurement method. At these levels the PM mass collected approaches the mass of non-particle gaseous species that adsorb onto the filter from exhaust and ambient air. This introduces an intrinsic lower limit to filter based measurement that is independent of improvements achieved in weighing metrology. The statistical variability of back-up filter measurements at these levels makes them an ineffective means for correcting the adsorption artifact. The proposed subtraction of a facility based estimate of the artifact will partially alleviate the mass bias from adsorption, but its impact on weighing variability remains a problem that can reach a significant fraction of the upcoming 3 and future 1 mg/mi standards. This paper proposes an improved PM mass method that combines the gravimetric filter approach with real time aerosol measurement.

The largest contribution to engine rubbing friction is made by the piston and piston rings running in the cylinder liner. The magnitude and characteristics of the friction behaviour and the influence on these of factors such as surface roughness, piston design and lubricant properties are of keen interest. Investigating presents experimental challenges, including potential problems of uncontrolled build-to-build variability when component changes are made. These are addressed in the design of a new motored piston and floating liner rig. The design constrains transverse movement of a single liner using cantilevered mounts at the top and bottom. The mounts and two high stiffness strain gauged load cells constrain vertical movement. The outputs of the load cells are processed to extract the force contribution associated with friction. The liner, piston and crankshaft parts were taken from a EuroV-compliant, HPCR diesel engine with a swept capacity of 550cc per cylinder.

Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.

Nowadays, an automotive DI Diesel engine is demanded to provide an adequate power output together with limit-complying NOx and soot emissions so that the development of a specific combustion concept is the result of a trade-off between conflicting objectives. In other words, the development of a low-emission DI diesel combustion concept could be mathematically represented as a multi-objective optimization problem. In recent years, genetic algorithm and CFD simulations were successfully applied to this kind of problem. However, combining GA optimization with actual CFD-3D combustion simulations can be too onerous since a large number of simulations is usually required, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes.